{"id":{"repo_id":"eastern-wash","oai_identifier":"oai:dc.ewu.edu:theses-1795"},"canonical_url":"https://search.dev.ndltd.org/etd/eastern-wash/oai:dc.ewu.edu:theses-1795","repository":{"repo_id":"eastern-wash","name":"Eastern Washington University","base_url":"https://dc.ewu.edu/do/oai/"},"display":{"title":"Word prediction in assistive technologies for Aphasia rehabilitation in using Systemic Functional Grammar","abstract":"<p>This work investigates the potential application of Natural Language Processing techniques in order to improve the effectiveness of assistive technologies in aphasia rehabilitation. Aphasia rehabilitation has predominately been centered on therapy sessions with speech language pathologists. While Augmentative and Alternative Communication (AAC) devices have made identifiable progress in providing support which is able to be managed by the individual, language production tasks are often challenged by the limitations brought about by aphasia. What follows is a description of a word prediction strategy based on Systemic Functional Grammar, which incorporates syntactic and contextual analysis; and its potential for aiding language production in assistive technologies</p>","abstract_html":"&lt;p&gt;This work investigates the potential application of Natural Language Processing techniques in order to improve the effectiveness of assistive technologies in aphasia rehabilitation. Aphasia rehabilitation has predominately been centered on therapy sessions with speech language pathologists. While Augmentative and Alternative Communication (AAC) devices have made identifiable progress in providing support which is able to be managed by the individual, language production tasks are often challenged by the limitations brought about by aphasia. What follows is a description of a word prediction strategy based on Systemic Functional Grammar, which incorporates syntactic and contextual analysis; and its potential for aiding language production in assistive technologies&lt;/p&gt;","abstract_has_math":false,"creators":["Sorna, Christopher T."],"institution":null,"degree_name":"Master of Science (MS) in Computer Science","degree_level":"Thesis: EWU Only","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-01-01T08:00:00Z","date_published":"2009-01-01T08:00:00Z","updated_at":"2026-07-24T02:12:46Z","subjects":["Communication Sciences and Disorders","Graphics and Human Computer Interfaces"],"languages":[],"rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://dc.ewu.edu/theses/793","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Sorna, Christopher T."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis: EWU Only"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science (MS) in Computer Science"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Communication Sciences and Disorders","Graphics and Human Computer Interfaces"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Access perpetually restricted to EWU users with an active EWU NetID"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://dc.ewu.edu/theses/793"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>This work investigates the potential application of Natural Language Processing techniques in order to improve the effectiveness of assistive technologies in aphasia rehabilitation. Aphasia rehabilitation has predominately been centered on therapy sessions with speech language pathologists. While Augmentative and Alternative Communication (AAC) devices have made identifiable progress in providing support which is able to be managed by the individual, language production tasks are often challenged by the limitations brought about by aphasia. What follows is a description of a word prediction strategy based on Systemic Functional Grammar, which incorporates syntactic and contextual analysis; and its potential for aiding language production in assistive technologies</p>"]},{"key":"dc:title","label":"Title","values":["Word prediction in assistive technologies for Aphasia rehabilitation in using Systemic Functional Grammar"]}]}],"canonical_facts":{"dc:creator":["Sorna, Christopher T."],"dc:description.abstract":["<p>This work investigates the potential application of Natural Language Processing techniques in order to improve the effectiveness of assistive technologies in aphasia rehabilitation. Aphasia rehabilitation has predominately been centered on therapy sessions with speech language pathologists. While Augmentative and Alternative Communication (AAC) devices have made identifiable progress in providing support which is able to be managed by the individual, language production tasks are often challenged by the limitations brought about by aphasia. What follows is a description of a word prediction strategy based on Systemic Functional Grammar, which incorporates syntactic and contextual analysis; and its potential for aiding language production in assistive technologies</p>"],"dc:identifier":["https://dc.ewu.edu/theses/793"],"dc:rights":["Access perpetually restricted to EWU users with an active EWU NetID"],"dc:subject":["Communication Sciences and Disorders","Graphics and Human Computer Interfaces"],"dc:title":["Word prediction in assistive technologies for Aphasia rehabilitation in using Systemic Functional Grammar"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis: EWU Only"],"thesis:degree_name":["Master of Science (MS) in Computer Science"]},"updated_at":"2026-07-24T02:12:46Z"}